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modeling Experience in plastic degradation or depolymerization Experience in bioinformatics, molecular modeling, or simulations Experience in experimental protein or enzyme characterization Track record
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water. The work is carried out by building optimization models and collecting data according to principles of open science. The analyses include sensitivity analysis, scenario building and analysis, and
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picture recognition. Strong background in machine learning, statistical modeling, and big-data analytics. Experience with infrastructure or transportation data or traffic planning (e.g. micro-simulation
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and in situ hybridization (including HCR) to localise cell types of interest in the eyes and optic lobes. These data will be compared with related model species with less complex eyes. Work duties The
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established in the areas of electronic and electromagnetic simulation and design, machine learning and artificial intelligence in electrical engineering, electrical low-frequency and high-frequency measurement
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several cancer research groups represented, including joint seminars and other collaborative activities. The group uses various data sources and modern techniques to improve predictive modelling, including
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theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms. Our research integrates expertise
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recruiting an outstanding and ambitious postdoctoral researcher in computational biology to advance the integration and modeling of large-scale microscopy data using modern machine learning approaches
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computational imaging specialist – experience in quantitative image analysis, scattering modeling, signal processing, machine learning, or neural-network-based data interpretation. The project is closely
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. This postdoctoral position at KTH focuses on developing advanced modelling frameworks and techno-economic analyses within two national research projects addressing virtual energy sharing and large-scale